Method and system for adapting an effective spreading sequence in a communication system using direct sequence spreading

ABSTRACT

A method and system for adapting an effective spreading sequence in a wire-line or a wireless communication system using direct sequence spreading system is described. A station of the communication system determines a state of a communication channel, represented by, e.g., an impulse response, a step response, or any other characteristic known to one skilled in the art. The station determines the channel state by measurements of a received signal or by receiving a feedback signal comprising an information enabling the station to determine the plurality of linearly related phases The station then determines a plurality of linearly related phases in accordance with the state of the communication channel, and then applies at least one of the plurality of linearly related phases to at least one sample of the effective spreading sequence.

BACKGROUND

1. Field

The present invention relates to a wire-line or a wireless communicationsystem using direct sequence spreading. More particularly, the presentinvention relates to a method and system for adapting an effectivespreading sequence in such a system.

2. Background

Communication systems have been developed to allow transmission ofinformation signals from an origination station to a physically distinctdestination station. In transmitting an information signal from theorigination station over a communication channel, the information signalis first converted into a form suitable for efficient transmission overthe communication channel. Conversion, or modulation, of the informationsignal involves varying a parameter of a carrier wave in accordance withthe information signal in such a way that the spectrum of the resultingmodulated carrier wave is confined within the communication channelbandwidth. At the destination station, the original information signalis reconstructed from the modulated carrier wave received over thecommunication channel. In general, such a reconstruction is achieved byusing an inverse of the modulation process employed by the originationstation.

Modulation also facilitates multiple-access, i.e., simultaneoustransmission and/or reception, of several signals over a commoncommunication channel. Several multiple-access techniques are known inthe art, such as time division multiple-access (TDMA), frequencydivision multiple-access (FDMA), code-division multiple-access (CDMA)spread spectrum system.

Originally, the multiple-access communication systems were designed tocarry analog signals (typically voice signals) between users. With thedevelopment of digital communication systems, there came the ability totransfer digital data representing any kind of information, and not onlyvoice information.

The above-discussed techniques apply equally to wireless and wire-basedcommunication systems. Wire-line communication systems transferinformation along a path constrained by a guide, e.g., a copper cable, afiber optic cable, said guide connecting the users; while wirelesscommunication systems transfer information along path between users notconstrained by any guide.

By way of example, in a multiple-access wireless communication system,communications between users on subscriber stations are conductedthrough an access network. A subscriber station is an entity with whichan access network communicates through a wireless path. A subscriberstation may be mobile or stationary. An access network is a collectionof at least one base station and one or more base stations' controllers.An access network transports information signals between users onsubscriber stations. The access network may be further connected toadditional networks outside the access network, such as a corporateintranet or the Internet, and may transport information signals betweeneach base station and such outside networks. A base station is an accessnetwork entity, with which subscriber stations communicate.

A first user on one wireless subscriber station communicates to a seconduser on a second wireless subscriber station by conveying an informationsignal on a reverse link to a base station. The base station receivesthe information signal and conveys the information signal on a forwardlink to the second subscriber station. If the second subscriber stationis not in the area served by the base station, the base station routesthe data to another base station, in whose service area the secondsubscriber station is located. The second base station then conveys theinformation signal on a forward link to the second subscriber station.The forward link refers to transmissions from a base station to awireless subscriber station, and the reverse link refers totransmissions from a wireless subscriber station to a base station.Likewise, the communication can be conducted between a first user on awireless subscriber station and a second user on a landline station. Abase station receives the data from the first user on the wirelesssubscriber station on a reverse link, and routes the data through apublic switched telephone network (PSTN) to the second user on alandline station.

It is well known that quality and effectiveness of information transferin a wireless communication system is dependent on the state of acommunication channel between a source terminal and a destinationterminal. Such a state can be represented as, for example, the channelimpulse response, an unit step response, a path loss and the path loss'variation at a subscriber station within a coverage area of a basestation, interference from other subscriber stations both from the samecell and from other cell, interference from other base stations, andother factors known to one of ordinary skill in the art. A designer of acommunication system can significantly increase the efficiency oftransmissions over a communication channel if the channel stateinformation can be used at the transmitter to adapt the transmittedsignal to the channel.

It is noted that the above discussed efficiency of signal transferapplies also for systems that do not “communicate” information per se,e.g., RADAR systems, because the effective transmission of the signalnon bearing information is still one of a primary issues. To preventobscuring the disclosure with excessive terminology repetition, the termcommunication system is used collectively for all types of systems.

One of the proposed approaches to utilize the channel state informationis to use filter matched to the channel. This approach results in a highpeak-to-average ratio of power required for transmission, and (forcertain modulation schemes) also in need for very linear transmitter.These requirements translate into very expensive transmitters.Furthermore, the amount of the channel state information necessary forproper determination of the matched filter is high, resulting in a highfeedback rate if the station utilizing the channel state information isnot the station determining the channel state information.

Another proposed approach, better suited to modulation schemes using adirect sequence spreading, is to adapt a spreading sequence to a channelby selecting, from a set of spreading sequences, the spreading sequencethat results in the best transmission efficiency in accordance with thechannel state information. An advantage of this approach is a lowerfeedback rate if the station utilizing the channel state information isnot the station determining the channel state information. However, theneed to change the spreading sequence causes several problems. As isexplained in detail below, one selection criterion selects the spreadingsequence, an autocorrelation function of which multiplied by anautocorrelation function of the channel impulse response yields amaximum. Clearly, to obtain such a sequence, the above-describedcomputation must be performed for each spreading sequence from the setof spreading sequences. The selection criterion is; therefore,computationally intensive.

Furthermore, such an optimal selection of a spreading sequence in amulti-user environment may result in selection of identical sequencesfor at least two users, causing increased interference. As aconsequence, should interference be avoided, optimal spreading sequenceassignment using this approach is not possible.

Because an insignificant number of currently used communication systemsbased on the CDMA standard known as IS-95 (“TIA/EIA/IS-95 MobileStation-Base Station Compatibility Standard for Dual-Mode Wide-BandSpread Spectrum Cellular System”) and CDMA2000 (“TR-45.5 Physical LayerStandard for CDMA2000 Spread Spectrum Systems”), as well ascommunication systems according to a standard known as W-CDMA, which isa CDMA-based standard (“3rd Generation Partnership Project” or “3GPP,”see for example document nos. 3G TS 25.211, 3G TS 25.212, 3G TS 25.213,and 3G TS 25.214), utilize direct sequence spreading, there is a need inthe art for an apparatus and method for adapting a spreading sequence toa channel in a communication system.

SUMMARY

In one aspect of the invention, a method for adapting an effectivespreading sequence in a communication system is disclosed. The methodcomprises determining a state of a communication channel and determininga plurality of linearly related phases in accordance with the state ofthe communication channel. The method further comprises applying atleast one of the plurality of linearly related phases to at least onesample of the effective spreading sequence.

In another aspect of the invention, an apparatus for adapting aneffective spreading sequence in a communication system is disclosed. Theapparatus comprises means for determining a state of a communicationchannel and means for determining a plurality of linearly related phasesin accordance with the state of the communication channel. The apparatusfurther comprises means for applying at least one of the plurality oflinearly related phases to at least one sample of the effectivespreading sequence.

In another aspect of the invention, a method for adapting an effectivespreading sequence in a communication system is disclosed. The methodcomprises receiving a feedback signal comprising information enablingdetermination of a plurality of linearly related phases and determiningthe plurality of linearly related phases in accordance with thefeedback. The method further comprises applying at least one of theplurality of linearly related phases to at least one sample of theeffective spreading sequence.

In another aspect of the invention, an apparatus for adapting aneffective spreading sequence in a communication system is disclosed. Theapparatus comprises means for receiving a feedback signal comprisinginformation enabling determination of a plurality of linearly relatedphases and means for determining the plurality of linearly relatedphases in accordance with the feedback. The apparatus further comprisesmeans for applying at least one of the plurality of linearly relatedphases to at least one sample of the effective spreading sequence.

BRIEF DESCRIPTION OF THE DRAWINGS

The features of the invention are set forth with particularity in theappended claims and together with advantages thereof will become clearerfrom consideration of the following detailed description of an exemplaryembodiment of the invention given with reference to the accompanyingdrawings.

FIG. 1 illustrates a conceptual diagram of a communication system;

FIG. 2 illustrates a model of channel state of an exemplary operatingenvironment in a form of a multi-path delay profile;

FIG. 3 illustrates a conceptual diagram of a communication system foradapting an effective spreading sequence; and

FIG. 4 illustrates a concept of effective spreading sequence.

DETAILED DESCRIPTION

FIG. 1 illustrates a conceptual diagram of a communication systemcomprising transmitting station 102 and a receiving station 108. Thetransmitting station 102 comprises a block 104 representing atransmitter, which transmits information signal d spread with aneffective spreading sequence s(t), denoted d·s(t). Signal d may comprisea digital signal. In general, a digital signal is processed before beingspread. Such a processing may comprise digitization of originally analogsignal, interleaving, encoding, and other processing known in the art;however, such processing is not shown for clarity reasons. The variablet denotes continuous time.

An effective spreading sequence s(t) used to spread the signal d maycomprise a sequence used to distinguish different channels, e.g., Walshcode, a Hadamard code, an orthogonal variable spreading factor (OVSF)code, and the like, or it may comprise a product of a sequence used todistinguish different channels with one or more scrambling sequences, asdescribed in greater details below. The terms spreading sequence andspreading code are used interchangeably in the art.

By way of example, in a communication system according to the IS-95 andIS-2000 standards a scrambling sequence may comprise a long code; in acommunication system according to the WCDMA standard a scramblingsequence may comprise a long scrambling sequence.

As the spread signal d·s(t) propagates through a block 106 representinga channel, the spread signal d·s(t) is modified by the channel inaccordance with the channel state; thus the receiving station 108receives this modified signal e(t). As discussed above, a state of thechannel may be represented by, e.g., an impulse response, an unit stepresponse, or any other representations known to one skilled in the art.The term channel state will be used collectively for channel state andchannel state representation, unless a use of the collective term wouldcause a confusion. For tutorial reasons an impulse response h(t) will beused. Then, the modified signal e(t) can be described by Equation (1):e(t)=d·s(t)*h(t)  (1)where the symbol * indicates convolution.

It is customary to evaluate performance of a receiving station inaccordance with the despread signal. A conceptual diagram of a receivingstation 108 comprises block 110 representing a receiver-filter, block112 representing a despreader, block 114 representing a switch, andblock 116 representing a switch control. The conceptual diagram of thereceiving station 108 corresponds to a Rake receiver.

The block 110 may be characterized by, e.g., impulse response, unit stepresponse, or any other characteristic known to one skilled in the art.For tutorial reasons a complex conjugate h*(T_(f)−t) of the channelimpulse response h(t) will be used. The variable T_(f) denotes durationof the channel impulse response and assures in mathematical descriptioncausality of a system. Because the communication system must be causal,to simplify mathematical notation, the complex conjugate of the impulseresponse is hereafter denoted as h*(−t). The block 110 outputs signalr(t) that can be described by Equation (2):r(t)=d·s(t)*h(t)*h*(−t)  (2)

The block 112 may comprise a matched filter and may be characterized by,e.g., impulse response, unit step response, or any other characteristicknown to one skilled in the art, matched to the received effectivespreading sequence. For descriptive reasons a complex conjugates*(T_(d)−t) of the spreading sequence impulse response s(t) will beused. The variable T_(d) denotes an integration period of the block 112.For the same reasons stated regarding T_(f), the variable T_(d) will beomitted to simplify mathematical notation, and the complex conjugate ofthe impulse response is hereafter denoted as s*(−t). A signal v(t) atthe output of the block 112 can be described by Equation (3):v(t)=d·s(t)*h(t)*h*(−t)*s*(−t)=d·C _(ss)(t)*C _(hh)(t)  (3)where:

C_(ss)(t) is a value of an aperiodic autocorrelation of the effectivespreading sequence; and

C_(hh)(t) is a value of an aperiodic autocorrelation of the impulseresponse of the communication channel.

As is well known in the art, the discrete-time aperiodic autocorrelationof the effective spreading sequence can be expressed as Equation (4):

$\begin{matrix}{{C_{ss}(m)} = {{\sum\limits_{n = 0}^{{SF} - 1 - m}{{{s^{*}(n)} \cdot {s\left( {n + m} \right)}}\mspace{14mu}{for}\mspace{14mu} m}} \geq 0}} & (4)\end{matrix}$Similarly, discrete-time aperiodic autocorrelation of the channelimpulse response can be expressed as Equation (5):

$\begin{matrix}{{C_{hh}(m)} = {{\sum\limits_{n = 0}^{L - 1 - m}{{{h^{*}(n)} \cdot {h\left( {n + m} \right)}}\mspace{14mu}{for}\mspace{14mu} m}} \geq 0}} & (5)\end{matrix}$where:

SF is the spreading factor; and

L is the length in T_(d) of the channel impulse response.

Note that C_(hh)(−m)=C*_(hh)(m) and C_(ss)(−m)=C*_(ss)(m). Spreadingfactor is a number of chips of a spreading sequence per unit of a spreaddigital signal. The term “chip” is a unit of a spreading sequence signalhaving at least two possible values.

The signal v(t) is sampled by the block 114 at intervals correspondingto the integration period T_(d). The intervals corresponding to theintegration period T_(d) are controlled by block 116, which providesproper sampling signal to the block 114. The signal at the output of theblock 114 represents the signal v(t) evaluated at discrete intervalsl·T_(d), where l is an integer number. Because the time dependency is ofno concern in the following description, the continuous time variable tmay be replaced with a sample index variable m. Equation (3) can then bere-written as Equation (6):

$\begin{matrix}{v = {d{\sum\limits_{m}{{C_{ss}(m)} \cdot {C_{hh}^{*}(m)}}}}} & (6)\end{matrix}$where C_(hh)(m) and C_(ss)(m) now denote the discrete-time aperiodicautocorrelation function defined below. The summation is done over all mfor which the argument of the summation does not vanish.

As discussed, performance of a transmission scheme is evaluated by amagnitude of a despread signal at a receiving station; the higher themagnitude, the better the performance at the receiving station. FromEquation (6) we obtain the magnitude:

$\begin{matrix}{v^{\prime} = {{Re}\left( {\sum\limits_{m}{{C_{ss}(m)} \cdot {C_{hh}^{*}(m)}}} \right)}} & (7)\end{matrix}$where Re( ) denotes real part of the term in parenthesis; and

m is a summation index, for which the argument of the summation does notvanish.

Given the definition of C_(hh)(m) and C_(ss)(m) above, and consideringthat the term for sample index m=0 in Equation (6) does not depend onthe spreading code since C_(ss)(0) is independent of the spreading codeand, therefore, the corresponding term does not need to be considered, mattains values 1≦m≦k where k=min(SF−1;L−1)

Considering the possibility of maximizing Equation (7), the termC_(hh)(m) in Equation (7) corresponding to the autocorrelation C_(hh)(t)is determined by the channel state. However, the transmitting station102 has control over the autocorrelation C_(ss)(t) corresponding to theterm C_(ss)(m) in the Equation (7). The term C_(ss)(m) can be changed byadapting the sequence s(t). Thus, Equation (7) may be maximized byadapting the sequence s(t) so that the product of the aperiodicautocorrelations is maximal.

The sequence s(t) may be adapted by linear phase adaptation, i.e., byapplying at least one of the plurality of linearly related phases to atleast one sample of the effective spreading sequence. Although thesequence s(t) is continuous in time, only the value of the sequence ats(m) is important. One way of adaptation is multiplication, in whichcase the adapted sequence s′(m) can be expressed by Equation (8):s′(m)=e ^(jθ(m)) ·s(m)  (8)where: j=sqrt(−1);

-   -   m is the sample index; and    -   θ(m) is the m-th of the plurality of phases.

Because the sequence s(m) comprises, in general, a complex number, whichcan be expressed as a phasor, the multiplication is equivalent toapplying a phase shift to each of the samples.

For the purposes of further analysis, the phase may be defined byEquation (9):

$\begin{matrix}{{\theta(m)} = \frac{2{\pi\alpha}\; m}{M}} & (9)\end{matrix}$where: α is a phase factor; and

-   -   M is the number of phases.

In general, there is no limitation on the selection of M and acorresponding set of phase factors α. Consequently, phases θ(m) mayattain any of M values from 0 to 2·π radians. The need for sucharbitrary phases may not be a problem in newly designed communicationsystems; however, certain existing communication system may takeadvantage of limiting the set of values the phases θ(m) may attain. Forexample, by limiting the number of values for the phase factor α to M=4,and selecting a value of the phase factor α from the set {0,1,2,3}limits the number of phases to

$\left\{ {0,\frac{\pi}{4},\pi,{3 \cdot \frac{\pi}{4}}} \right\}$radians. Such a selection corresponds to a quadrature-phase shift keying(QPSK) modulation. It is noted; however, that such a selection of theset of values for the phase factor α is not a limitation of the phaseadaptation algorithm, but rather an implementation issue.

The autocorrelation function C_(s′s′)(m) for the adapted sequence s′(m)is expressed by Equation (9) for m≧0:

$\begin{matrix}{{C_{S^{\prime}S^{\prime}}(m)} = {{\sum\limits_{n = 0}^{{SF} - 1 - m}{{{\mathbb{e}}^{\frac{{- j}\; 2{\pi\alpha}\; n}{M}} \cdot {s^{*}(n)} \cdot {\mathbb{e}}^{\frac{{j2\pi}{({\alpha{({n + m})}})}}{M}}}{s\left( {n + m} \right)}}} = {{\mathbb{e}}^{\frac{j\; 2{\pi\alpha}\; m}{M}} \cdot {{C_{SS}(m)}.}}}} & (10)\end{matrix}$Substituting Equation (10) to Equation (7) yields Equation (11) for theterm to be maximized:

$\begin{matrix}{v^{\prime} = {{{Re}\left( {\sum\limits_{m = 1}^{k}{{C_{s^{\prime}s^{\prime}}(m)}{C_{hh}^{*}(m)}}} \right)} = {{Re}\left( {\sum\limits_{m = 1}^{k}{{\mathbb{e}}^{\frac{j\; 2{\pi\alpha}\; m}{M}}{C_{ss}(m)}{C_{hh}^{*}(m)}}} \right)}}} & (11)\end{matrix}$

As noted in analysis of Equation (7), equally applicable to Equation(11), to maximize the equation by adapting the effective spreadingsequence in a communication system, the term C_(ss)(m) must becalculated. As described above, C_(ss)(m) is calculated for all sampleindexes m in accordance with Equation (4) from an impulse response ofthe effective spreading sequence.

Additionally, a communication channel state must be determined. Then theterm C_(hh)(m) is derived from the channel state. As discussed above,for tutorial purposes an impulse response was used as a representationof the channel state. However, any other representation with a definedrelationship to impulse response, e.g., step response, allowingderivation of the term C_(hh)(m) can be used.

The channel state may be determined, e.g., from a measurement of achannel by a channel estimation unit. Such an approach takes advantageof the fact that a channel estimation unit is present in many modernreceiver stations (see, e.g., FIG. 3, block 330, described below), andyields a very accurate impulse response estimate, which improvesefficiency of the adaptation in an operating environment of thecommunication system, in which the channel state change rapidly. Once animpulse response is obtained, C_(hh)(m) is calculated for each of theplurality of indexes m in accordance with Equation (5).

Once the values of the aperiodic autocorrelations C_(ss)(m) andC_(hh)(m) are determined, the different phases maximizing Equation (11)can be determined. Because the different phases are linearly relatedthrough the phase factor α, maximizing Equation (11) can be viewed asdetermining the value of the phase factor α that yields a maximum ofEquation (11). Accordingly, the calculated aperiodic autocorrelationsC_(ss)(m) and C_(hh)(m) are substituted into Equation (11), and Equation(11) is solved for the value of the phase factor α that yields a maximumof Equation (11).

Once the linearly related phases are determined, at least one of thelinearly related phases is applied to at least one sample of theeffective spreading sequence.

Alternatively, the value of the first sample, i.e., the sample withindex m=0, is excluded from the calculated aperiodic autocorrelation ofthe impulse response of the communication channel C_(hh)(m). Then, themaximum magnitude value from the remaining samples of the aperiodicautocorrelation C_(hh)(m) is determined. This value, with sample indexm_(max), is denoted C_(hh)(m_(max)). The value of the aperiodicautocorrelation C_(ss)(m_(max)) is then determined, and the plurality oflinearly related phases is determined in accordance with theC_(hh)(m_(max)) and the C_(ss)(m_(max)) Accordingly, equation (11) canthen be approximated by Equation (12):

$\begin{matrix}{v^{\prime} = {{Re}\left( {{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{{C_{ss}\left( m_{\max} \right)} \cdot {C_{hh}^{*}\left( m_{\max} \right)}}} \right)}} & (12)\end{matrix}$Equation (12) is solved for the value of the phase factor α that yieldsa maximum of Equation (12).

It can be shown that a solution of Equation (12) for the value of thephase factor α that yields a maximum of Equation (12) only requires thevalues of the phases of C_(ss)(m_(max)) and C*_(hh)(m_(max)).Mathematically, finding a maximum of Equation (12) is equivalent tofinding minimum of the expression

$\begin{matrix}{\left( {{\,^{\frac{2{\pi\alpha}\; m_{\max}}{M}}{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right),} & \;\end{matrix}$where arc( ) identifies the phase of the argument in the parenthesis.

Alternatively, the indexes m₁, m₂>m₁, corresponding to the two largestmagnitudes of the of the impulse response h(m) are determined.Considering Equation (5), the only non-zero value of the aperiodicautocorrelation C_(hh)(m) for m≠0 occurs for m_(max)=m₂−m₁, and can becalculated from the values h(m₁) and h(m₂). The value of the aperiodicautocorrelation C_(ss)(m_(max)) is then determined, and the plurality oflinearly related phases is determined in accordance with theC_(hh)(m_(max)) and the C_(ss)(m_(max)). Accordingly, Equation (12) issolved for the value of the phase factor α that yields a maximum ofEquation (12).

It can be shown that a solution of Equation (12) for the value of thephase factor a that yields a maximum of Equation (12) only requires thevalues of the phases of C_(ss)(m_(max)) and C*_(hh)(m_(max)).Mathematically, finding a maximum of Equation (11) is equivalent tofinding minimum of the expression

$\left( {{\,^{\frac{2{\pi\alpha}\; m_{\max}}{M}}{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right).$Because the phase of C*_(hh)(m_(max)) is equal to the phase differenceof h(m₁) and h(m₂) without a sign, it is not necessary to evaluateC*_(hh)(m_(max))

Once the phase factor α, or equivalently the values of correspondingphases θ(m) are determined as described above, the adapted sequence s(m)can be calculated form Equation (8).

In a class of communication systems, the communication channel state isdifferent for a transmission channel and a reception channel from theperspective of a communication station. By way of example, in aFrequency Division Duplex (FDD) communication system, the communicationstations are allocated separate frequencies for transmission andreception. The separate frequencies may be so far apart in the frequencyspectrum that the state of the communication channel modulated at thetransmission frequency is different from the state of the communicationchannel modulated at the reception frequency, the difference beinggreater than an acceptable error margin.

To allow such communication systems to take advantage of effectivespreading sequence adaptation, a measure assuring that the plurality oflinearly related phases is common to a transmitting communicationstation and a receiving communication station must be implemented.

According to one such measure, a first communication station receiving acommunication channel modulated at a first frequency determines a stateof the communication channel. The first communication station thendetermines a plurality of linearly related phases in accordance with thestate of the communication channel and reports (feeds back), over acommunication channel modulated on a second frequency, informationenabling a second communication station to determine the plurality oflinearly related phases.

The second communication station receiving signal comprising thefeedback information, determines the plurality of linearly relatedphases in accordance with the feedback information, and applies at leastone of the plurality of linearly related phases to at least one sampleof the effective spreading sequence. As follows from Equation (8) thefirst communication station and the second communication station mustadapt the respective spreading sequence with a different sign of theplurality of linearly related phases.

The feedback information enabling the second communication station todetermine the plurality of linearly related phases may comprise at leastone of the plurality of phases θ.

Because the phases are linearly related, when the first communicationstation and the second communication station agree in advance on thenumber of phases M and the set of phase factors α, feedback informationcomprising only one of the plurality of phases θ(m) is sufficient.Additionally, if the effective spreading sequence is invariable, i.e.,the spreading sequence does not change from a digital data unit to adigital data unit, the one of the plurality of phases θ(m) is the samefor all digital data units.

Alternatively, if the effective spreading sequence is variable, i.e.,the spreading sequence does change form a digital data unit to a digitaldata unit, the one of the plurality of phases θ(m) may be re-determinedand fed back for each of the variable effective spreading sequence upondetecting a change in the state of the communication channel.

Alternatively, the feedback information enabling the secondcommunication station to determine the plurality of linearly relatedphases may comprise the phase factor α. An advantage of this approach isthat the second communication station need not carry out anycomputation. Additionally, if the effective spreading sequence isinvariable, i.e., the spreading sequence does not change from a digitaldata unit to a digital data unit, phase factor α is the same for alldigital data units. This yields a relatively low feedback update ratebecause phase factor α need to be re-determined only upon detecting achange in the state of the communication channel.

Alternatively, if the effective spreading sequence is variable, i.e.,the spreading sequence does change form a digital data unit to a digitaldata unit, the phase factor α may be re-determined and fed back for eachof the variable effective spreading sequence upon detecting a change inthe state of the communication channel. This yields a relatively higherfeedback.

To lower the feedback in this scenario, the phase factor α may bere-determined and fed back only for one of the variable effectivespreading sequences upon detecting a change in the state of thecommunication channel. Accordingly, upon detecting a change in the stateof the communication channel, the receiving station determines thechannel state. The receiving station then calculates a phase factor α₁for one of the variable effective spreading sequences characterized byan autocorrelation C_(ss) ₁ (m) in accordance with the determinedchannel state represented by, e.g., an autocorrelation C_(hh)(m). Thedetermined channel state together with the phase factor α₁ and,optionally the value of C_(ss) ₁ (m), are then communicated to thetransmitting station.

Both the receiving station and the transmitting station use thedetermined channel state, the phase factor α₁ and, optionally the valueof C_(ss) ₁ (m), and as input parameters to a statistical model of theautocorrelation function of the communication channel to calculate thephase factors α_(k), where k denotes the remaining effective spreadingsequences.

It is noted that a design of the statistical model is a design choice,dependent e.g., on the sophistication of the designer, availablecomputing power, complexity of the determined channel state, and thelike. However, in a way of example, several models are presented.

For a determined channel state represented by, e.g., only two non-zerosamples, a reference index m_(ref) is set to equal a value of 1 when thetwo non-zero samples are consequent, and to equal a value of m_(max) (asdefined above) otherwise. For a determined channel state represented bymore than two non-zero samples, a reference index m_(ref) is expressedby Equation (13):m _(ref)=max(|C _(ss) ₁ (m)|√{square root over (SF−m)}) for ∀m  (13)

The phase factors α_(k) are then determined as phase factors minimizingthe difference between the phase values determined for α₁ and C_(ss) ₁(m), i.e.,

$\left( {{\mathbb{e}}^{\frac{{j2\alpha}_{1}\pi\; m_{ref}}{M}} \cdot {C_{{ss}_{1}}\left( m_{ref} \right)}} \right)$and for α_(k) and C_(ss) _(k) (m), i.e.,

$\left( {{\mathbb{e}}^{\frac{{j2\alpha}_{k}\pi\; m_{ref}}{M}} \cdot {C_{{ss}_{k}}\left( m_{ref} \right)}} \right).$

Alternatively, the feedback information may comprise the communicationchannel state, e.g., the impulse response, itself. It is noted that itis not necessary to communicate the complete representation of thecommunication channel state. As described above, it may be sufficient tocommunicate information about the indices of the two largest magnitudesof the impulse response. The phase factor α is then determined asdescribed above. The phase factor α is updated according to theabove-described considerations.

To further decrease the feedback associated with communicating thecommunication channel state, an alternative way of determining thechannel state may be used. It has been observed that certain operatingenvironment(s) of the communication system yield typical, fairlyinvariable channel state. Such a channel state can be pre-determined ina form of a model for different operating environments in accordancewith simulations, laboratory experiments, field trials and otherengineering methods known in the art.

By way of example, FIG. 2 illustrates one such model of a channel statein a form of a multi-path delay profile. The multi-path delay profile isa statistical model comprising expected powers determined from animpulse response of an exemplary, e.g., indoor, operating environment.As can be observed FIG. 4, where the normalization

${\sum\limits_{m}{{h(m)}}^{2}} = 1$is used, the 0-th sample of the impulse response has an expected powerof approximately E(|h(0)|²=0.9, the 1st sample of the impulse responsehas an expected power of approximately E(|h(1)|²=0.099, and the rest ofthe expected power is distributed among the remaining samples. Becausethe expected power contribution from the remaining samples is below apower threshold, these samples may be omitted. Consequently, the modelof the channel state has only few non-zero samples. It is noted that thepower threshold is a design criterion.

The use of such a model, agreed upon by both the transmitting stationand the receiving station, decreases the amount of feedback requiredbecause the channel state to be used can be determined from the modeland several parameters specifying the model based on the channel state.By way of an example, the model from FIG. 2 would be specified bymeasurement of phases of the non-zero samples, and only a phasedifference between these samples needs to be determined andcommunicated.

By way of example, a first station of the communication systemdetermines an operating environment and selects a pre-determined channelstate model in accordance with the determined operating environment. Thefirst station then communicates the selected model, or an identifier ofthe selected model, to the other station(s) in the communication system.Afterwards, the first station measures the channel state andcommunicates to the other station(s) only the minimum parameters of thechannel state required for reconstruction of the channel state from themodel and the communicated parameters at the other station(s).

Alternatively, the feedback information may comprise the aperiodicautocorrelation of the impulse response of the communication channelC_(hh)(m). Again, it is not necessary to communicate the completeaperiodic autocorrelation of the impulse response. As described above,it may be sufficient to convey information about the first maxima of theimpulse response. The phase factor α is then determined from thereceived aperiodic autocorrelation of the impulse response. The phasefactor α is updated according to the above-described considerations.

FIG. 3 illustrates a conceptual block of a communication system foradapting an effective spreading sequence, which may be utilized in a FDDcommunication system. Although a cellular wireless communication systemterminology is used, such is just for tutorial purpose; any directsequence (DS) CDMA communication system that allows providing feedbackinformation from a receiving station to the transmitting station can beused.

To prevent obscuring the description of FIG. 3 with undue details, thefirst communication station is referred to as a receiving station 324and shows only the structure facilitating the reception function.Likewise, the second communication station is referred to as atransmitting station 302, and only the structure facilitating thetransmission function is shown. However, since the communication isbi-directional, the transmitting station 302 also comprises thestructure facilitating the reception function, and the receiving station324 also comprises the structure facilitating the reception function.

The transmitting station 302 comprises a block 304 representing a sourceof data and any processing of the data that may be carried out beforemodulation. As discussed above, such a processing may comprisedigitization of originally analog signal, interleaving, encoding, andother processing known in the art. The processed data is provided to ablock 306, which modulates the processed data. The modulation is carriedout in accordance with the communication system's modulation format. Themodulated data are provided to a block 308, which spreads the modulateddata with a spreading sequence provided from block 308. The spread datais provided to block 312, which adapts the spread data by phases θ(m)provided from block 314. The phases θ(m) are determined in accordancewith the information provided from a block 316, representing a feedbackreceiver. It is noted that the division of function between blocks 316and 314 is rather artificial for purposes of explanation. The functionof the block 314 may be in optionally performed by block 316. Theadapted spread data is provided to a block 318, which scrambles theadapted spread data with a scrambling sequence provided from block 320.The scrambled data is provided to a block 322, which transmits thescrambled data.

It is well known in the art that the sequence in which the blocks 308,312, and 318 (as well as associated blocks 310, 314, and 320), operateon the modulated data is changeable. As such blocks 308 and 318 can beviewed as generating an effective spreading sequence, and block 312 asadapting the effective spreading sequence.

FIG. 4 illustrates a concept of an effective spreading sequence. Thedata to be spread, e.g., the modulated data described in reference toFIG. 3, are organized in units identified as 402(n−2) to 402(n+3) oflength T_(d), expressed in chips. Such a unit may comprise, e.g., a datasymbol. As discussed above, the units 402(n−2) to 402(n+3) may comprisedigital data, therefore, the term digital data unit may also be used.The spreading sequence 404 comprising, e.g., Walsh code, a Hadamardcode, an orthogonal variable spreading factor (OVSF) code, or the like,is the same for each of the units 402(n−2) to 402(n+3). The scramblingsequence 406 comprising, e.g. a long code used in a communication systemaccording to IS-95, IS-2000 standards, has a period of length T_(S),expressed in chips. The spreading sequence 404 and the scramblingsequence 406 combine into an effective spreading sequence 408, which isthen used to spread the units 402(n−2) to 402(n+3). It can be observedthat the effective spreading sequence 408 repeats itself every periodT_(S), and may be different for each of the units of length T_(d) withinthe period T_(S). It is, of course, possible to add as many scramblingsequences as possible.

It is noted that an effective spreading sequence with propertiesdescribed above, e.g., repeating itself every period T_(S) and generallydifferent for each of the units of length T_(d) within the period T_(S),may be obtained by different structures. Thus for example, referringback to FIG. 3, the blocks 320 and 318 could be deleted, and the block310 could be configured to generate a pattern comprising a differentspreading sequence in every unit of length T_(d) within the periodT_(S), the pattern being repeated every period T_(S).

Alternatively, the block 310 could be configured to generate the samespreading sequence in every unit of length T_(d) regardless of theperiod T_(S).

Alternatively, the block 310 could be configured to generate a differentspreading sequence in every unit of length T_(d) regardless of theperiod T_(S).

The receiving station 324 comprises a Rake receiver, represented by theblocks 328(i), 330, 332(i), 340(i), 344, and 348 with supportingstructure and function represented by blocks 334(i), 336, and 338.Because structure and function of Rake receiver are well known in theart, the Rake receiver is described only in a manner allowingunderstanding of the structure and function of the blocks 334(i), 336,and 338.

The signal received over a channel by a block 326, representing anantenna and a front end of the Rake receiver, is divided and provided toblocks 330 and 328(i).

Block 330 represents a channel estimation unit, which determines thechannel state by measurements of the received signal. The determinedchannel state is provided to blocks 338 and 344.

Block 338 represents a determination unit, which determines informationenabling determination of the plurality of linearly related phases inaccordance with the channel state as described above. The information isthen provided to block 336, described below. Furthermore, the block 338provides feedback information to a block 316 in the transmitting station302. The provided feedback information allows the transmitting station302 to determine the plurality of linearly related phases as describedabove. It is noted that the division of function between blocks 336 and338 is rather artificial for purposes of explanation. The function ofthe block 336 may be optionally performed by block 338.

Each of the blocks 328(i), 332(i), 334(i), and 340(i) identified by thesame index i represents a part of an individual Rake receiver finger. Ingeneral a rake receiver comprises more than one finger, i.e., i>1;however, the number of fingers is not limitation on the use of the phaseadaptation. A finger is a structure allowing a Rake receiver process oneof the multiple paths over which a signal with identical informationpropagated from a transmitting station to a receiving station. Eachblock 328(i) delays the data from the individual multi-path, which arethen de-scrambled in a block 332(i) using a scrambling sequencegenerated by block 348.

If more than one scrambling sequence (see FIG. 4 and associated text)was used at the transmitting station 302, the structure, comprisingblock 232(i) and a scrambling sequence generated by block 334(i) isprovided at the receiver for each of the scrambling sequence.

Similarly, should the block 320 be deleted and the block 310 beconfigured to generate a pattern comprising a different spreadingsequence in every unit of length T_(d) within the period T_(S), thepattern being repeated every period T_(S) at the transmitting station302, the structure at the receiving station 324, comprising blocks332(i) and a scrambling sequence generated by block 234(i) can bedeleted, and the block 342 could be configured to generate a patterncomprising a different spreading sequence in every unit of length T_(d)within the period T_(S).

Alternatively, the block 342 could be configured to generate the samespreading sequence in every unit of length T_(d) regardless of theperiod T_(S), or to generate a different spreading sequence in everyunit of length T_(d) regardless of the period T_(S).

The descrambled data are then provided to blocks 334(i), which adapt thedescrambled data by a phase θ(m) provided from block 336. The adaptationis carried out by applying at least one of the plurality of linearlyrelated phases to at least one sample of the digital data unit. Block336 determines phase θ(m) in accordance with the feedback informationprovided by block 338 as described above.

The adapted descrambled data are then provided to blocks 340(i)representing despreaders, where the adapted descrambled data aredespread with a spreading sequence provided from block 342. The despreadsymbols are provided to a combiner 344, which combines the symbols inaccordance with a channel characteristic provided by the block 330. Thecombined data are then provided to block 346 representing a demodulator,and the demodulated data are provided for further processing (notshown).

Because the above-described interchangeability of the sequence of(de)scrambling, (de)spreading, and phase adapting operations, theabove-described processing can be interpreted as adapting the adaptedspreading sequence to arrive at the original spreading sequence. Thus ona conceptual level, the processing at the receiving station is alsoeffective spreading sequence adaptation.

In contrast to the above-mentioned communication systems, there existcommunication systems in which the state of the communication channel issimilar (within acceptable error margin) for forward and reversechannel. In such a communication system, each of the communicationstation communicating with one another is likely to arrive with the sameestimate of the channel state. Because the estimate of the channel stateis likely the same at the communication stations communicating with oneanother, the communication stations may perform the above-describedapplication of the linear phase shift to an effective spreading sequencewithout the need for a feedback.

An example of such a communication system is a Time Division Duplex(TDD) communication system, in which the stations are allocated the samefrequency for transmission and reception.

Because no feedback is needed, referring back to FIG. 3, the conceptualmodel of receiving station and a transmitting station is similar to thetransmitting station 302 and the receiving station 324, except the block316 representing the feedback receiver is absent; and block 338 isconnected directly to block 314.

A receiving communication station receives signal comprising user datafrom a transmitting communication station. The signal comprising datawas arranged by the transmitting station in accordance with principlesdescribed in reference to FIG. 1 and FIG. 3 above. Thus both thetransmitting station 302 and the receiving station 324 determine stateof a communication channel in accordance with the above-describedconcepts. Both communication stations then determine a plurality oflinearly related phases in accordance with the above-described concepts.Both communication stations then apply at least one of the plurality oflinearly related phases to at least one sample of the effectivespreading sequence. As disclosed above, each of the transmitting station302 and the receiving station 324 applies the at least one of theplurality of linearly related phases with an opposite sign.

As discussed above, in communication systems, in which the state of thecommunication channel is similar (within acceptable error margin) forforward and reverse channel, the stations communicating with one anotherare likely to arrive with the same estimate of the channelcharacteristic. Such an estimate is highly dependent on channel state,e.g., a scatterer structure Therefore, with high probability only thecommunicating stations arrive with the same estimate of the channelstate, and consequently, the choice of the same spreading code. As such,the used spreading code is changed depending on a “shared secret” (thechannel characteristic), which is not known to third parties, i.e.,other than the communicating stations.

This mechanism may be used to make interception of this communicationdifficult for the third parties, especially with selection of M as alarge number because then even the below described improved blinddetermination becomes computationally infeasible.

It is, nevertheless, possible, that the receiving station does not knowwhich adapted sequence s′(m) was used by the transmitting station. Forexample, in a TDD communication system the stations communicating withone another arrive with a different channel characteristic. Or, therewas a feedback error in the FDD system. Under such a condition thereceiving station may request re-transmission of information whichadapted sequence s′(m) was used by the transmitting station or attempt ablind determination of the transmitted signal.

In general, a blind detection performs despreading and followingsampling operation (see, FIG. 1 and associated text), for each of thepossible M adapted sequences s′(m), and selecting that adapted sequences′(m), which yielded the largest magnitude. This approach iscomputationally very expensive, especially for larger number M.

Mathematically, the despreading and sampling operation can be expressedby Equation (14), where m_(l) denotes the delays corresponding to eachof the blocks 328(i) of FIG. 3:

$\begin{matrix}{{{\sum\limits_{m = 0}^{{SF} - 1}{{{\mathbb{e}}^{\frac{{- {j2\pi}}\mspace{11mu} i\mspace{11mu} m}{M}} \cdot {s^{*}(m)} \cdot {r\left( {m - m_{l}} \right)}}\mspace{14mu}{for}\mspace{14mu} i}} = 0},1,\ldots\mspace{11mu},{M - 1}} & (14)\end{matrix}$Considering Equation (14) it can be observed that rather than evaluatingeach equation separately, and taking the maximum value as prior artblind detection suggest, implementation of these evaluations can besimplified using the well-known Fast Fourier Transform (FFT) technique,see., e.g., “Discrete-Time Signal Processing,” by Oppenheimer andSchafer, published by Prentice Hall.

The above-described concepts are valid for any communication systemutilizing direct-sequence spread spectrum, and references to particularembodiments of a communication system, e.g., a wireless cellularcommunication system, have been made only for tutorial purposes.

The previous description of the disclosed embodiments is provided toenable any person skilled in the art to make or use the presentinvention. Various modifications to these embodiments will be readilyapparent to those skilled in the art, and the generic principles definedherein may be applied to other embodiments without departing from thescope of the embodiments. Thus, the present invention is not intended tobe limited to the embodiments shown herein but is to be accorded thewidest scope consistent with the principles and novel features disclosedherein.

1. A method for adapting an effective spreading sequence in acommunication system, comprising: using a channel estimation unit fordetermining a state of a communication channel by a. determining anoperating environment of the communication system; b. selecting apre-determined model for the state of the communication channel inaccordance with said determined operating environment; c. determiningparameters of the pre-determined model in accordance with the state ofthe communication channel; and d. determining the state of thecommunication channel from the parameters and the pre-determined model;and using a determination unit for determining a plurality of linearlyrelated phases in accordance with the state of the communication channeland for applying at least one of the plurality of linearly relatedphases to at least one sample of the effective spreading sequence togenerate an adapted spreading sequence, wherein the adapted spreadingsequence is used to despread a received signal.
 2. The method as claimedin claim 1 further comprising: transmitting a feedback signal comprisingsaid selected pre-determined model; and transmitting a feedback signalcomprising said determined parameters.
 3. A method for adapting aneffective spreading sequence in a communication system, comprising:using a channel estimation unit for determining a state of acommunication channel; and using a determination unit for determining aplurality of linearly related phases in accordance with the state of thecommunication channel by a. determining a value of a phase shift factorα that maximizes the expression:${Re}\left( {\sum\limits_{m}{{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m}{M}}{C_{ss}(m)}{C_{hh}^{*}(m)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; in is anindex; M is number of phases; * identifies a complex conjugate;C_(ss)(m) is a value of an aperiodic autocorrelation of the effectivespreading sequence; and C_(hh)(m) is a value of an aperiodicautocorrelation of an impulse response of the communication channel; andb. determining the plurality of linearly related phases in accordancewith the phase shift factor α; and using the determination unit forapplying at least one of the plurality of linearly related phases to atleast one sample of the effective spreading sequence to generate anadapted spreading sequence, wherein the adapted spreading sequence isused to despread a received signal.
 4. A method for adapting aneffective spreading sequence in a communication system, comprising:using a channel estimation unit for determining a state of acommunication channel; and using a determination unit for determining aplurality of linearly related phases in accordance with the state of thecommunication channel by a. calculating for each of a plurality ofindexes in a corresponding value of an a periodic autocorrelation of animpulse response of the communication channel C_(hh)(m); b. determiningan index m_(max)>0 for which a magnitude of the value C_(hh)(m) attainsmaximum; c. determining a value of an aperiodic autocorrelation of aneffective spreading sequence C_(ss)(m_(max)); and d. determining theplurality of linearly related phases in accordance with theC_(hh)(m_(max)) and the C_(ss)(m_(max)); and using the determinationunit for applying at least one of the plurality of linearly relatedphases to at least one sample of the effective spreading sequence togenerate an adapted spreading sequence, wherein the adapted spreadingsequence is used to despread a received signal.
 5. The method as claimedin claim 4, wherein said determining the plurality of linearly relatedphases in accordance with the C_(hh)(m_(max)) and the C_(ss)(m_(max))comprises: determining a value of a phase shift factor α that maximizesthe expression:${Re}\left( {{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{{C_{ss}\left( m_{\max} \right)} \cdot {C_{hh}^{*}\left( m_{\max} \right)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; M is number ofphases; * identifies a complex conjugate; and determining the pluralityof linearly related phases in accordance with the phase shift factor α.6. The method as claimed in claim 4, wherein said determining theplurality of linearly related phases in accordance with theC_(hh)(m_(max)) and the C_(ss)(m_(max)) comprises: determining a phaseof C_(hh)(m_(max)); determining a phase of C_(ss)(m_(max)); anddetermining the plurality of linearly related phases in accordance withthe phases of C_(hh)(m_(max)) and the C_(ss)(m_(max)).
 7. The method asclaimed in claim 6, wherein said determining the plurality of linearlyrelated phases in accordance with the phases of C_(hh)(m_(max)) and theC_(ss)(m_(max)) comprises: determining a value of a phase shift factor αthat minimizes the expression:$\left( {{\,^{\frac{2{\pi\alpha}\; m_{\max}}{M}}{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right)$wherein: M is number of phases; arc( ) is a phase of the argument; *identifies a complex conjugate; and determining the plurality oflinearly related phases in accordance with the phase shift factor α. 8.A method for adapting an effective spreading sequence in a communicationsystem, comprising: using a channel estimation unit for determining astate of a communication channel; and using a determination unit fordetermining a plurality of linearly related phases in accordance withthe state of the communication channel by a. determining indexes m₁ andm₂ for the largest and the second largest magnitudes of an impulseresponse of the communication channel h(m); b. calculating an aperiodicautocorrelation of the impulse response of the communication channelC_(hh)(m_(max)), wherein m_(max)=m₁−M₂; c. calculating an aperiodicautocorrelation of an effective spreading sequence C_(ss)(m_(max)); andd. determining the plurality of linearly related phases in accordancewith the C_(hh)(m_(max)) and the C_(ss)(m_(max)); and using thedetermination unit for applying at least one of the plurality oflinearly related phases to at least one sample of the effectivespreading sequence to generate an adapted spreading sequence, whereinthe adapted spreading sequence is used to despread a received signal. 9.The method as claimed in claim 8, wherein said determining the pluralityof linearly related phases in accordance with the C_(hh)(m_(max)) andthe C_(ss)(m_(max)) comprises: determining a value of a phase shiftfactor α that maximizes the expression:${Re}\left( {e^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{{C_{ss}\left( m_{\max} \right)} \cdot {C_{hh}^{*}\left( m_{\max} \right)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; M is number ofphases; * identifies a complex conjugate; and determining the pluralityof linearly related phases in accordance with the phase shift factor α.10. A method for adapting an effective spreading sequence in acommunication system, comprising: using a channel estimation unit fordetermining a state of a communication channel; and using adetermination unit for determining a plurality of linearly relatedphases in accordance with the state of the communication channel by a.determining indexes m₁ and m₂ for the largest and the second largestmagnitudes of an impulse response of the communication channel h(m); b.determining a phase of C_(hh)(m_(max)), wherein m_(max)=m₁−m₂; c.determining a phase of C_(ss)(m_(max)); and d. determining the pluralityof linearly related phases in accordance with the phases ofC_(hh)(m_(max)) and the C_(ss)(m_(max)); and using the determinationunit for applying at least one of the plurality of linearly relatedphases to at least one sample of the effective spreading sequence togenerate an adapted spreading sequence, wherein the adapted spreadingsequence is used to despread a received signal.
 11. The method asclaimed in claim 10, wherein said determining the plurality of linearlyrelated phases in accordance with the phases of C_(hh)(m_(max)) and theC_(ss)(m_(max)) comprises: determining a value of a phase shift factor αthat minimizes the expression:$\left( {{\,^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right.$wherein: M is number of phases; arc( ) is a phase of the argument; *identifies a complex conjugate; and determining the plurality oflinearly related phases in accordance with the phase shift factor α. 12.The method as claimed in claim 10, wherein said determining the phase ofC_(hh)(m_(max)) comprises: determining the phase difference betweenh(m₁) and h(m₂).
 13. A method for adapting an effective spreadingsequence in a communication system, comprising: using a channelestimation unit for determining a state of a communication channel; andusing a determination unit for determining a plurality of linearlyrelated phases in accordance with the state of the communication channeland for applying at least one of the plurality of linearly relatedphases to at least one sample of the effective spreading sequence togenerate an adapted spreading sequence by evaluating for each index m anequation:s′(m)=e ^(jθ(m)) ·s(m) wherein: s′(m) is the adapted spreading sequence;s(m) is the effective spreading sequence; j is an imaginary unit;${\theta(m)} = \frac{2{\pi\alpha}\; m}{M}$  is the m-th phase; α is aphase factor; and M is number of phases, and wherein the adaptedspreading sequence is used to despread a received signal.
 14. A methodfor adapting an effective spreading sequence in a communication system,comprising: using a channel estimation unit for determining a state of acommunication channel; and using a determination unit for determining aplurality of linearly related phases in accordance with the state of thecommunication channel and for applying at least one of the plurality oflinearly related phases to at least one sample of the effectivespreading sequence to generate an adapted spreading sequence byevaluating for each index m an equation:s′(m)=e ^(−jθ(m)) ·s(m) wherein: s′(m) is the adapted spreadingsequence; s(m) is the effective spreading sequence; j is an imaginaryunit; ${\theta(m)} = \frac{2{\pi\alpha}\; m}{M}$  is the m-th phase; αis a phase factor; and M is number of phases, and wherein the adaptedspreading sequence is used to despread a received signal.
 15. Anapparatus for adapting an effective spreading sequence in acommunication system, comprising: means for determining a state of acommunication channel which includes: a. means for determining anoperating environment of the communication system; b. means forselecting a pre-determined model for the state of the communicationchannel in accordance with said determined operating environment; c.means for determining parameters of the pre-determined model inaccordance with the state of the communication channel; and d. means fordetermining the state of the communication channel from the parametersand the pre-determined model; means for determining a plurality oflinearly related phases in accordance with the state of thecommunication channel; and means for applying at least one of theplurality of linearly related phases to at least one sample of theeffective spreading sequence.
 16. The apparatus as claimed in claim 15further comprising: means for transmitting a feedback signal comprisingsaid selected pre-determined model; and means for transmitting afeedback signal comprising said determined parameters.
 17. An apparatusfor adapting an effective spreading sequence in a communication system,comprising: means for determining a state of a communication channel;means for determining a plurality of linearly related phases inaccordance with the state of the communication channel, the meansincluding: a. means for determining a value of a phase shift factor αthat maximizes the expression:${Re}\left( {\sum\limits_{m}{{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m}{M}}{C_{ss}(m)}{C_{hh}^{*}(m)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; m is an index;M is number of phases; * identifies a complex conjugate; C_(ss)(m) is avalue of an aperiodic autocorrelation of the effective spreadingsequence; and C_(hh)(m) is a value of an aperiodic autocorrelation of animpulse response of the communication channel; and b. means fordetermining the plurality of linearly related phases in accordance withthe phase shift factor α; and means for applying at least one of theplurality of linearly related phases to at least one sample of theeffective spreading sequence.
 18. An apparatus for adapting an effectivespreading sequence in a communication system, comprising: means fordetermining a state of a communication channel means for determining aplurality of linearly related phases in accordance with the state of thecommunication channel, the means including: a. means for calculating foreach of a plurality of indexes m a corresponding value of an aperiodicautocorrelation of an impulse response of the communication channelC_(hh)(m); b. means for determining an index m_(max)>0 for which amagnitude of the value C_(hh)(m) attains maximum; c. means fordetermining a value of an aperiodic autocorrelation of an effectivespreading sequence C_(ss)(m_(max)); and d. means for determining theplurality of linearly related phases in accordance with theC_(hh)(m_(max)) and the C_(ss)(m_(max)); and means for applying at leastone of the plurality of linearly related phases to at least one sampleof the effective spreading sequence.
 19. The apparatus as claimed inclaim 18, wherein said means for determining the plurality of linearlyrelated phases in accordance with the C_(hh)(m_(max)) and theC_(ss)(m_(max)) comprise: means for determining a value of a phase shiftfactor α that maximizes the expression:${Re}\left( {{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{{C_{ss}\left( m_{\max} \right)} \cdot {C_{hh}^{*}\left( m_{\max} \right)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; M is number ofphases; * identifies a complex conjugate; and means for determining theplurality of linearly related phases in accordance with the phase shiftfactor α.
 20. The apparatus as claimed in claim 18, wherein said meansfor determining the plurality of linearly related phases in accordancewith the C_(hh)(m_(max)) and the C_(ss)(m_(max)) comprise: means fordetermining a phase of C_(hh)(m_(max)); means for determining a phase ofC_(ss)(m_(max)); and means for determining the plurality of linearlyrelated phases in accordance with the phases of C_(hh)(m_(max)) and theC_(ss)(m_(max)).
 21. The apparatus as claimed in claim 20, wherein saidmeans for determining the plurality of linearly related phases inaccordance with the phases of C_(hh)(m_(max)) and the C_(ss)(m_(max))comprise: means for determining a value of a phase shift factor α thatminimizes the expression:$\left( {}^{\frac{2{\pi\alpha}\; m_{\max}}{M}}{{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right)$wherein: M is number of phases; arc( ) is a phase of the argument; *identifies a complex conjugate; and means for determining the pluralityof linearly related phases in accordance with the phase shift factor α.22. An apparatus for adapting an effective spreading sequence in acommunication system, comprising: means for determining a state of acommunication channel; means for determining a plurality of linearlyrelated phases in accordance with the state of the communicationchannel, the means including: a. means for determining indexes m₁ and m₂for the largest and the second largest magnitudes of an impulse responseof the communication channel h(m); b. means for calculating an aperiodicautocorrelation of the impulse response of the communication channelC_(hh)(m_(max)), wherein m_(max)=m₁−m₂; c. means for calculating anaperiodic autocorrelation of an effective spreading sequenceC_(ss)(m_(max)); and d. means for determining the plurality of linearlyrelated phases in accordance with the C_(hh)(m_(max)) and theC_(ss)(m_(max)); and means for applying at least one of the plurality oflinearly related phases to at least one sample of the effectivespreading sequence.
 23. The apparatus as claimed in claim 22, whereinsaid means for determining the plurality of linearly related phases inaccordance with the C_(hh)(m_(max)) and the C_(ss)(m_(max)) comprise:means for determining a value of a phase shift factor α that maximizesthe expression:${Re}\left( {{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{{C_{ss}\left( m_{\max} \right)} \cdot {C_{\;^{hh}}^{*}\left( m_{\max} \right)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; M is number ofphases; * identifies a complex conjugate; and means for determining theplurality of linearly related phases in accordance with the phase shiftfactor α.
 24. An apparatus for adapting an effective spreading sequencein a communication system, comprising: means for determining a state ofa communication channel; means for determining a plurality of linearlyrelated phases in accordance with the state of the communicationchannel, the means including: a. means for determining indexes m₁ and m₂for the largest and the second largest magnitudes of an impulse responseof the communication channel b. means for determining a phase ofC_(hh)(m_(max)), wherein m_(max)=m₁−m₂; c. means for determining a phaseof C_(ss)(m_(max)); and d. means for determining the plurality oflinearly related phases in accordance with the phases of C_(hh)(m_(max))and the C_(ss)(m_(max)); and means for applying at least one of theplurality of linearly related phases to at least one sample of theeffective spreading sequence.
 25. The apparatus as claimed in claim 24,wherein said means for determining the plurality of linearly relatedphases in accordance with the phases of C_(hh)(m_(max)) and theC_(ss)(m_(max)) comprise: means for determining a value of a phase shiftfactor α that minimizes the expression:$\left( {}^{\frac{2{\pi\alpha}\; m_{\max}}{M}}{{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right.$wherein: M is number of phases; arc( ) is a phase of the argument; *identifies a complex conjugate; and means for determining the pluralityof linearly related phases in accordance with the phase shift factor α.26. The apparatus as claimed in claim 24, wherein said means fordetermining the phase of C_(hh)(m_(max)) comprise: means for determiningthe phase difference between h(m₁) and h(m₂).
 27. An apparatus foradapting an effective spreading sequence in a communication system,comprising: means for determining a state of a communication channel;means for determining a plurality of linearly related phases inaccordance with the state of the communication channel; means forapplying at least one of the plurality of linearly related phases to atleast one sample of the effective spreading sequence, the meansincluding means for evaluating for each index m an equation:s′(m)=e ^(jθ(m)) ·s(m) wherein: s′(m) is the adapted spreading sequence;s(m) is the effective spreading sequence; j is an imaginary unit;${\theta(m)} = \frac{2{\pi\alpha}\; m}{M}$  is the m-th phase; α is aphase factor; and M is number of phases.
 28. An apparatus for adaptingan effective spreading sequence in a communication system, comprising:means for determining a state of a communication channel; means fordetermining a plurality of linearly related phases in accordance withthe state of the communication channel; means for applying at least oneof the plurality of linearly related phases to at least one sample ofthe effective spreading sequence, the means including means forevaluating for each index m an equation:s′(m)=e ^(−jθ(m)) ·s(m) wherein: s′(m) is the adapted spreadingsequence; s(m) is the effective spreading sequence; j is an imaginaryunit; ${\theta(m)} = \frac{2{\pi\alpha}\; m}{M}$  is the m-th phase; αis a phase factor; and M is number of phases.
 29. A method for adaptingan effective spreading sequence in a communication system, comprising:using a feedback receiver for receiving a feedback signal comprising aphase factor α and information enabling determination of a plurality oflinearly related phases; determining the plurality of linearly relatedphases in accordance with the feedback by evaluating for each index m anequation: ${{\theta(m)} = \frac{2{\pi\alpha}\; m}{M}};$ wherein: M isnumber of phases; and using a multiplier for applying at least one ofthe plurality of linearly related phases to at least one sample of theeffective spreading sequence to generate an adapted spreading sequence,wherein the adapted spreading sequence is used to spread a transmitsignal.
 30. The method as claimed in claim 29, wherein said applying atleast one of the plurality of linearly related phases to at least onesample of the effective spreading sequence comprises: evaluating foreach index m an equation:s′(m)=e ^(jθ(m)) ·s(m) wherein: s′(m) is the adapted spreading sequence;s(m) is the effective spreading sequence; j is an imaginary unit. 31.The method as claimed in claim 29, wherein said applying at least one ofthe plurality of linearly related phases to at least one sample of theeffective spreading sequence comprises: evaluating for each index m anequation:s′(m)=e ^(−jθ(m)) ·s(m) wherein: s′(m) is the adapted spreadingsequence; s(m) is the effective spreading sequence; j is an imaginaryunit.
 32. A method for adapting an effective spreading sequence in acommunication system, comprising: using a feedback receiver forreceiving a feedback signal comprising information enablingdetermination of a plurality of linearly related phases wherein thefeedback signal comprising a pre-determined model characterizing thecommunication channel and at least one parameter of the pre-determinedmodel; determining the plurality of linearly related phases inaccordance with the feedback; and using a multiplier for applying atleast one of the plurality of linearly related phases to at least onesample of the effective spreading sequence to generate an adaptedspreading sequence, wherein the adapted spreading sequence is used tospread a transmit signal.
 33. The method as claimed in claim 32, whereinsaid determining the plurality of linearly related phases comprises:determining an aperiodic autocorrelation of an impulse responseC_(hh)(m) of the communication channel in accordance with thepre-determined model and the parameters; determining a value of a phaseshift factor α that maximizes the expression:${Re}\left( {\sum\limits_{m}{{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m}{M}}{C_{ss}(m)}{C_{hh}^{*}(m)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; m is an index;M is number of phases, * identifies a complex conjugate; C_(ss)(m) is avalue of an aperiodic autocorrelation of the effective spreadingsequence; and determining the plurality of linearly related phases inaccordance with the phase shift factor α.
 34. The method as claimed inclaim 32, wherein said determining the plurality of linearly relatedphases comprises: calculating for each of a plurality of indexes m acorresponding value of an aperiodic autocorrelation of an impulseresponse C_(hh)(m) of the communication channel in accordance with thepre-determined model and the parameters; determining an index m_(max)>0for which a magnitude of the value C_(hh)(m) attains maximum;determining a value of an aperiodic autocorrelation of an effectivespreading sequence C_(ss)(m_(max)); and determining the plurality oflinearly related phases in accordance with the C_(hh)(m_(max)) and theC_(ss)(m_(max)).
 35. The method as claimed in claim 34, wherein saiddetermining the plurality of linearly related phases in accordance withthe C_(hh)((m_(max)) and the C_(ss)(m_(max)) comprises: determining avalue of a phase shift factor α that maximizes the expression:${Re}\left( {\sum\limits_{m}{{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{{C_{ss}\left( m_{\max} \right)} \cdot {C_{hh}^{*}\left( m_{\max} \right)}}}} \right)$wherein: Re identifies real part; j is an imaginary unit; M is number ofphases; * identifies a complex conjugate; and determining the pluralityof linearly related phases in accordance with the phase shift factor α.36. The method as claimed in claim 34, wherein said determining theplurality of linearly related phases in accordance with theC_(hh)(m_(max)) and the C_(ss)(m_(max)) comprises: determining a phaseof C_(hh)(m_(max)); determining a phase of C_(ss)(m_(max)); anddetermining the plurality of linearly related phases in accordance withthe phases of C_(hh)(m_(max)) and the C_(ss)(m_(max)).
 37. The method asclaimed in claim 36, wherein said determining the plurality of linearlyrelated phases in accordance with the phases of C_(hh)(m_(max)) and theC_(ss)(m_(max)) comprises: determining a value of a phase shift factor αthat minimizes the expression:$\left( {}^{\frac{2{\pi\alpha}\; m_{\max}}{M}}{{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right)$wherein: M is number of phases; arc( ) is a phase of the argument; *identifies a complex conjugate; and determining the plurality oflinearly related phases in accordance with the phase shift factor α. 38.The method as claimed in claim 32, wherein said determining theplurality of linearly related phases comprises: determining an impulseresponse of the communication channel h(m) in accordance with thepre-determined model and the parameters; determining indexes m₁ and m₂for the largest and the second largest magnitudes of the impulseresponse of the communication channel h(m); calculating an aperiodicautocorrelation of the impulse response of the communication channelC_(hh)(m_(max)), wherein m_(max)=m₁−m₂; calculating an aperiodicautocorrelation of an effective spreading sequence C_(ss)(m_(max)); anddetermining the plurality of linearly related phases in accordance withthe C_(hh)(m_(max)) and the C_(ss)(m_(max)).
 39. The method as claimedin claim 38, wherein said determining the plurality of linearly relatedphases in accordance with the C_(hh)(m_(max)) and the C_(ss)(m_(max))comprises: determining a value of a phase shift factor α that maximizesthe expression:${Re}\left( {{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{{C_{ss}\left( m_{\max} \right)} \cdot {C_{hh}^{*}\left( m_{\max} \right)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; M is number ofphases; * identifies a complex conjugate; and determining the pluralityof linearly related phases in accordance with the phase shift factor α.40. A method for adapting an effective spreading sequence in acommunication system, comprising: using a feedback receiver forreceiving a feedback signal comprising information enablingdetermination of a plurality of linearly related phases; determining theplurality of linearly related phases in accordance with the feedback bya. determining an impulse response of the communication channel h(m) inaccordance with a pre-determined model and parameters; b. determiningindexes m₁ and m₂ for the largest and the second largest magnitudes ofthe impulse response of the communication channel h(m); c. determining aphase of C_(hh)(m_(max)), wherein m_(max)=m₁−m₂; d. determining a phaseof C_(ss)(m_(max)); and e. determining the plurality of linearly relatedphases in accordance with the phases of C_(hh)(m_(max)) and theC_(ss)(m_(max)); and using a multiplier for applying at least one of theplurality of linearly related phases to at least one sample of theeffective spreading sequence to generate an adapted spreading sequence,wherein the adapted spreading sequence is used to spread a transmitsignal.
 41. The method as claimed in claim 40, wherein said determiningthe plurality of linearly related phases in accordance with the phasesof C_(hh)(m_(max)) and the C_(ss)(m_(max)) comprises: determining avalue of a phase shift factor α that minimizes the expression:$\left( {}^{\frac{2{\pi\alpha}\; m_{\max}}{M}}{{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right)$wherein: M is number of phases; arc( ) is a phase of the argument; *identifies a complex conjugate; and determining the plurality oflinearly related phases in accordance with the phase shift factor α. 42.The method as claimed in claim 40, wherein said determining the phase ofC_(hh)(m_(max)) comprises: determining the phase difference betweenh(m₁) and h(m₂).
 43. A method for adapting an effective spreadingsequence in a communication system, comprising: using a feedbackreceiver for receiving a feedback signal comprising information enablingdetermination of a plurality of linearly related phases; determining theplurality of linearly related phases in accordance with the feedback;and using a multiplier for applying at least one of the plurality oflinearly related phases to at least one sample of the effectivespreading sequence to generate an adapted spreading sequence, whereinthe adapted spreading sequence is used to spread a transmit signal byevaluating for each index m an equation:s′(m)=e ^(jθ(m)) ·s(m) wherein: s′(m) is the adapted spreading sequence;s(m) is the effective spreading sequence; j is an imaginary unit;${\theta(m)} = \frac{2{\pi\alpha}\; m}{M}$  is the m-th phase; α is aphase factor; and M is number of phases.
 44. A method for adapting aneffective spreading sequence in a communication system, comprising:using a feedback receiver for receiving a feedback signal comprisinginformation enabling determination of a plurality of linearly relatedphases; determining the plurality of linearly related phases inaccordance with the feedback; and using a multiplier for applying atleast one of the plurality of linearly related phases to at least onesample of the effective spreading sequence to generate an adaptedspreading sequence, wherein the adapted spreading sequence is used tospread a transmit signal by evaluating for each index m an equation:s′(m)=e ^(−jθ(m)) ·s(m) wherein: s′(m) is the adapted spreadingsequence; s(m) is the effective spreading sequence; j is an imaginaryunit; ${\theta(m)} = \frac{2{\pi\alpha}\; m}{M}$  is the m-th phase; αis a phase factor; and M is the number of phases.
 45. An apparatus foradapting an effective spreading sequence in a communication system,comprising: means for receiving a feedback signal comprising informationenabling determination of a plurality of linearly related phases,wherein the feedback signal comprises a phase factor α; means fordetermining the plurality of linearly related phases in accordance withthe feedback, the means including means for evaluating for each index man equation: ${{\theta(m)} = \frac{2{\pi\alpha}\; m}{M}};$ wherein: M isnumber of phases; and means for applying at least one of the pluralityof linearly related phases to at least one sample of the effectivespreading sequence.
 46. The apparatus as claimed in claim 45, whereinsaid means for applying at least one of the plurality of linearlyrelated phases to at least one sample of the effective spreadingsequence comprise: means for evaluating for each index m an equation:s′(m)=e ^(jθ(m)) ·s(m) wherein: s′(m) is the adapted spreading sequence;s(m) is the effective spreading sequence; j is an imaginary unit. 47.The apparatus as claimed in claim 45, wherein said means for applying atleast one of the plurality of linearly related phases to at least onesample of the effective spreading sequence comprise: means forevaluating for each index m an equation:s′(m)=e ^(jθ(m)) ·s(m) wherein: s′(m) is the adapted spreading sequence;s(m) is the effective spreading sequence; j is an imaginary unit.
 48. Anapparatus for adapting an effective spreading sequence in acommunication system, comprising: means for receiving a feedback signalcomprising information enabling determination of a plurality of linearlyrelated phases wherein the feedback signal comprises a pre-determinedmodel characterizing the communication channel; and at least oneparameter of the pre-determined model; means for determining theplurality of linearly related phases in accordance with the feedback;and means for applying at least one of the plurality of linearly relatedphases to at least one sample of the effective spreading sequence. 49.The apparatus as claimed in claim 48, wherein said means for determiningthe plurality of linearly related phases comprise: means for determiningan aperiodic autocorrelation of an impulse response C_(hh)(m) of thecommunication channel in accordance with the pre-determined model andthe parameters; means for determining a value of a phase shift factor αthat maximizes the expression:${Re}\left( {\sum\limits_{m}{{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{C_{ss}(m)}{C_{hh}^{*}(m)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; m is an index;M is number of phases; * identifies a complex conjugate; C_(ss)(m) is avalue of an aperiodic autocorrelation of the effective spreadingsequence; and means for determining the plurality of linearly relatedphases in accordance with the phase shift factor α.
 50. The apparatus asclaimed in claim 48, wherein said means for determining the plurality oflinearly related phases comprise: means for calculating for each of aplurality of indexes m a corresponding value of an aperiodicautocorrelation of an impulse response C_(hh)(m) of the communicationchannel in accordance with the pre-determined model and the parameters;means for determining an index m_(max)>0 for which a magnitude of thevalue C_(hh)(m) attains maximum; means for determining a value of anaperiodic autocorrelation of an effective spreading sequenceC_(ss)(m_(max)); and means for determining the plurality of linearlyrelated phases in accordance with the C_(hh)(m_(max)) and theC_(ss)(m_(max)).
 51. The apparatus as claimed in claim 50, wherein saidmeans for determining the plurality of linearly related phases inaccordance with the C_(hh)((m_(max)) and the C_(ss)(m_(max)) comprise:means for determining a value of a phase shift factor α that maximizesthe expression:${Re}\left( {{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{{C_{ss}\left( m_{\max} \right)} \cdot {C_{hh}^{*}\left( m_{\max} \right)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; M is number ofphases; * identifies a complex conjugate; and means for determining theplurality of linearly related phases in accordance with the phase shiftfactor α.
 52. The apparatus as claimed in claim 50, wherein said meansfor determining the plurality of linearly related phases in accordancewith the C_(hh)(m_(max)) and the C_(ss)(m_(max)) comprise: means fordetermining a phase of C_(hh)(m_(max)); means for determining a phase ofC_(ss)(m_(max)); and means for determining the plurality of linearlyrelated phases in accordance with the phases of C_(hh)(m_(max)) and theC_(ss)(m_(max)).
 53. The apparatus as claimed in claim 52, wherein saidmeans for determining the plurality of linearly related phases inaccordance with the phases of C_(hh)(m_(max)) and the C_(ss)(m_(max))comprise: means for determining a value of a phase shift factor α thatminimizes the expression:$\left( {}^{\frac{2{\pi\alpha}\; m_{\max}}{M}}{{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right)$wherein: M is number of phases; arc( ) is a phase of the argument; *identifies a complex conjugate; and means for determining the pluralityof linearly related phases in accordance with the phase shift factor α.54. The apparatus as claimed in claim 48, wherein said means fordetermining the plurality of linearly related phases comprise: means fordetermining an impulse response of the communication channel h(m) inaccordance with the pre-determined model and the parameters; means fordetermining indexes m₁ and m₂ for the largest and the second largestmagnitudes of the impulse response of the communication channel h(m);means for calculating an aperiodic autocorrelation of the impulseresponse of the communication channel C_(hh)(m_(max)), whereinm_(max)=m₁−m₂; means for calculating an aperiodic autocorrelation of aneffective spreading sequence C_(ss)(_(max)); and means for determiningthe plurality of linearly related phases in accordance with theC_(hh)(_(max)) and the C_(ss)(m_(max)).
 55. The apparatus as claimed inclaim 54, wherein said means for determining the plurality of linearlyrelated phases in accordance with the C_(hh)(m_(max)) and theC_(ss)(m_(max)) comprise: means for determining a value of a phase shiftfactor α that maximizes the expression:${Re}\left( {{\mathbb{e}}^{\frac{{j2\pi\alpha}\; m_{\max}}{M}}{{C_{ss}\left( m_{\max} \right)} \cdot {C_{hh}^{*}\left( m_{\max} \right)}}} \right)$wherein: Re identifies real part; j is an imaginary unit; M is number ofphases; * identifies a complex conjugate; and means for determining theplurality of linearly related phases in accordance with the phase shiftfactor α.
 56. An apparatus for adapting an effective spreading sequencein a communication system, comprising: means for receiving a feedbacksignal comprising information enabling determination of a plurality oflinearly related phases; means for determining the plurality of linearlyrelated phases in accordance with the feedback, the means including a.means for determining an impulse response of the communication channelh(m) in accordance with a pre-determined model and parameters; b. meansfor determining indexes m₁ and m₂ for the largest and the second largestmagnitudes of the impulse response of the communication channel c. meansfor determining a phase of C_(hh)(m_(max)), wherein m_(max)=m₁−m₂; d.means for determining a phase of C_(ss)(m_(max)); and e. means fordetermining the plurality of linearly related phases in accordance withthe phases of C_(hh)(m_(max)) and the C_(ss)(_(max)); and means forapplying at least one of the plurality of linearly related phases to atleast one sample of the effective spreading sequence.
 57. The apparatusas claimed in claim 56, wherein said means for determining the pluralityof linearly related phases in accordance with the phases ofC_(hh)(m_(max)) and the C_(ss)(m_(max)) comprise: means for determininga value of a phase shift factor α that minimizes the expression:$\left( {}^{\frac{2{\pi\alpha}\; m_{\max}}{M}}{{+ {{arc}\left( {C_{ss}\left( m_{\max} \right)} \right)}} + {{arc}\left( {C_{hh}^{*}\left( m_{\max} \right)} \right)}} \right.$wherein: M is number of phases; arc( ) is a phase of the argument; *identifies a complex conjugate; and means for determining the pluralityof linearly related phases in accordance with the phase shift factor α.58. The apparatus as claimed in claim 56, wherein said means fordetermining the phase of C_(hh)(m_(max)) comprise: means for determiningthe phase difference between h(m₁) and h(m₂).
 59. An apparatus foradapting an effective spreading sequence in a communication system,comprising: means for receiving a feedback signal comprising informationenabling determination of a plurality of linearly related phases; meansfor determining the plurality of linearly related phases in accordancewith the feedback; and means for applying at least one of the pluralityof linearly related phases to at least one sample of the effectivespreading sequence, including means for evaluating for each index m anequation:s′(m)=e ^(jθ(m)) ·s(m) wherein: s′(m) is the adapted spreading sequence;s(m) is the effective spreading sequence; j is an imaginary unit;${\theta(m)} = \frac{2{\pi\alpha}\; m}{M}$  is the m-th phase; α is aphase factor; and M is number of phases.
 60. An apparatus for adaptingan effective spreading sequence in a communication system, comprising:means for receiving a feedback signal comprising information enablingdetermination of a plurality of linearly related phases; means fordetermining the plurality of linearly related phases in accordance withthe feedback; and means for applying at least one of the plurality oflinearly related phases to at least one sample of the effectivespreading sequence including means for evaluating for each index m anequation:s′(m)=e ^(−jθ(m)) ·s(m) wherein: s′(m) is the adapted spreadingsequence; s(m) is the effective spreading sequence; j is an imaginaryunit; ${\theta(m)} = \frac{2{\pi\alpha}\; m}{M}$  is the m-th phase; αis a phase factor; and M is the number of phases.